A blockchain-based financial data processing system

Abstract

The application relates to the technical field of data processing, in particular to a financial data processing system based on a block chain, which comprises an access chain authorization module, a writing arbitration scheduling module, a voucher path identification module, a structure callback node module and a chained result output module. In the application, the field calling sequence difference, calling interval time difference and calling return content consistency of a node access behavior log are calculated to obtain a stability score, stable nodes are screened, a block access permission mapping is formed, a sorting label is constructed based on a transaction timestamp and a fund transaction amount to realize the sorting of concurrent transaction priorities, a public key address list and a multi-signature access threshold are dynamically matched and judged to form a link access path redirection, the possibility of data tampering by nodes is reduced, and sequence verification and index tracing are performed according to the block height of a chain segment, a relay node confirmation state and an end data field variation value, so that the tracing ability of financial transaction data is significantly improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and in particular to a financial data processing system based on a block chain. BACKGROUND

[0002] The technical field of data processing mainly involves the whole process of obtaining, cleaning, converting, storing, analyzing and outputting raw data, aiming to extract valuable information from massive, complex or heterogeneous data. This field covers data structure optimization, storage architecture design, data flow control, concurrent processing algorithm, data consistency guarantee mechanism and efficient query and retrieval method. Typical implementation methods include database management system-based data processing, batch processing and stream processing solutions supported by distributed computing platforms, and special data processing models for specific business scenarios. This technical field focuses on ensuring processing efficiency, accuracy and security, and realizing efficient organization and management of structured, semi-structured or unstructured data.

[0003] Among them, the financial data processing system is a data processing system for financial field business scenarios, mainly used for processing large-scale financial data including transaction records, risk indicators, market quotes, customer behavior, etc. The system supports risk assessment, transaction behavior audit, compliance detection, investment portfolio management, customer portrait generation, etc. through the collection, standardization processing, analysis and calculation and structured storage of financial data. Its design aims to meet the processing needs of high real-time, high reliability and high accuracy of financial business, and improve the ability of financial institutions in regulatory compliance, operation optimization and intelligent decision-making.

[0004] When processing financial data, the traditional processing system uses a unified standardized mode for the analysis and processing of transaction records and risk indicators and other data, without making fine distinctions and controls on node stability, concurrent transaction order and data access permissions. Since the node access stability is not evaluated and screened, unstable nodes are likely to continuously participate in data writing, increasing the risk of data anomalies and loss. In the concurrent transaction writing stage, the traditional system lacks a clear sorting mechanism for transaction priority, causing the processing of concurrent transaction requests to often appear in disordered sorting and resource competition, leading to data processing delay or even failure. The traditional system lacks specific hierarchical control of transaction access permissions, causing sensitive data to be exposed to improper access risks, reducing the security and compliance of financial data. For example, when a large number of fund transactions occur at the same time, if accurate sorting and permission control are not performed, it will cause difficulties in transaction audit and traceability, affecting the audit efficiency and risk prevention and control level of financial institutions. SUMMARY

[0005] The purpose of the present application is to solve the shortcomings in the prior art and to provide a financial data processing system based on a block chain.

[0006] To achieve the above object, the application adopts the following technical scheme: a financial data processing system based on a blockchain, the system comprising:

[0007] The access chain authorization module obtains the access behavior log record of the node in three periods, calculates the access stability score based on the field calling sequence difference value, the calling interval time difference value and the calling return content consistency proportion, screens the nodes with a score greater than a reference value, and generates a block access permission mapping group;

[0008] The write arbitration scheduling module calls the block access permission mapping group, calculates the priority score according to the transaction timestamp and the fund transaction amount, compares the priority scores in sequence to build a write queue, and generates a multi-node transaction write order queue;

[0009] The voucher path identification module calls the multi-node transaction write order queue, judges whether the access control level is less than the data sensitive level label, if it is less than, sets it as a read-only chain identification, if it is greater than or equal to, sets it as a full-chain traceability identification, and generates a voucher driving chain path label set;

[0010] The structure callback node module calls the voucher driving chain path label set, compares the access control level in the access voucher, judges whether it meets the multi-signature access threshold value set in the link, if it does not meet, appends a path redirection mark, builds a path state list, and generates an access chain redirection structure group.

[0011] The application improves that the block access permission mapping group comprises node behavior continuity score records, node period access stability labels and permission allocation level tables, the multi-node transaction write order queue comprises sorting priority label sets, cross-node time scheduling indexes and transaction conflict mediation identifiers, the voucher driving chain path label set specifically comprises chain access control marks, path selection level identifiers and voucher matching path comparison tables, and the access chain redirection structure group comprises redirection path mapping tables, path verification failure indexes and chain segment access fallback node sets.

[0012] The application improves that the access chain authorization module comprises:

[0013] The behavior log collection submodule obtains the access behavior log of the node in three consecutive periods, calls three data fields of transaction details records, account balance changes and credit risk scores, establishes an access record set according to the access behavior occurrence time sequence, and identifies and archives according to the data source node to generate an access behavior log summary table;

[0014] The stability score calculation submodule extracts the data call sequence, call time interval and result return content associated with each node based on the access behavior log summary table, respectively calculates the field sequence difference value, interval difference value and result consistency proportion, and obtains an access stability score value list by operation, establishes a score distribution set according to the concentration degree of the score value, and obtains a node stability score set;

[0015] The node permission screening submodule calls the node stability score set, compares each node score value with a set access stability reference value, selects the node with a score value higher than the reference value, marks the access permission level and constructs a node permission mapping sequence, and generates a block access permission mapping group.

[0016] The application improves that the write arbitration scheduling module comprises:

[0017] The time label extraction submodule calls the block access permission mapping group, obtains the corresponding transaction timestamp, network delay time, block packaging time consumption and fund transaction amount in the transaction data, matches the fields with the node identifier in the block access permission mapping group, and establishes a field comparison table between the transaction record and the node, and obtains a transaction parameter matching set;

[0018] The priority score calculation submodule calls the transaction parameter matching set, normalizes the difference value of the field, obtains the priority score value of the transaction by operation, and generates a transaction priority score set;

[0019] The sorting queue generation submodule generates a transaction priority score set based on the transaction priority score set, arranges the transaction numbers in descending order according to the score value of each transaction, generates a sorting index of the corresponding node identifier and transaction ID, constructs a transaction record sorting table, and obtains a multi-node transaction write order queue.

[0020] The application improves that the credential path identifier module comprises:

[0021] The field extraction submodule calls the multi-node transaction write order queue, extracts the access control level, resource path identifier code and effective time range three fields in the access credential, writes the field values into a unified structure index table and classifies and identifies them according to the transaction number, and generates a credential field index set;

[0022] The level comparison submodule based on the credential field index set, according to the access control level corresponding to each transaction credential, reads the data sensitive level label in the on-chain data structure, compares the two field values in sequence, judges whether the access control level is less than the data sensitive level label, and marks the comparison result state, and obtains a credential level comparison result set;

[0023] The path label generation submodule assigns a read-only chain label to records with an access control level lower than the data sensitivity level label according to the credential level comparison result set, and assigns a full-chain tracking label to the remaining records, classifies and combines the two types of chain access labels, and generates a credential-driven chain path label set.

[0024] The structure callback node module comprises:

[0025] The chain path extraction submodule calls the credential-driven chain path label set, reads the node public key address list in the associated path according to the path record marked with a full-chain tracking label, and archives the path in sequence to generate a node link address set;

[0026] The permission verification submodule obtains the access control level parameter in the access credential according to the node value of each path based on the node link address set, compares the parameter with the multi-sign access threshold value set by the link, calculates the path permission offset degree, judges whether the offset degree exceeds the access offset tolerance range value, and if so, marks the verification failure state to obtain a permission matching offset degree sequence;

[0027] The path state construction submodule calls the permission matching offset degree sequence, appends a path redirection label to the path identification according to the path record marked with a verification failure state, updates the path state index table, constructs a path state set in sequence, and generates an access chain redirection structure group.

[0028] The system further comprises:

[0029] The chain result output module calls the access chain redirection structure group, extracts the chain segment starting block height, relay node confirmation state code and terminal data field change value from the record marked as a valid path structure, performs structure order verification on the three fields, and writes the chain structure index queue to generate a chain transaction tracking path structure.

[0030] The chain transaction tracking path structure specifically refers to a chain data traceability path, a structure consistency mapping sequence and an output data change mapping diagram.

[0031] The chain result output module comprises:

[0032] The field extraction submodule calls the access chain redirection structure group, extracts the chain segment starting block height, relay node confirmation state code and terminal data field change value from the record marked as a valid path structure, and reconstructs the three fields into a structure unit in sequence to generate a chain structure field set.

[0033] The sequence verification submodule sequentially numbers the block height, relay status, and data change value in each structural unit according to the chain structure field set, determines whether the block height is the starting index of the path, whether the relay status is continuously increasing, and whether the data change value is less than the preset change tolerance value, and filters the structural units that meet the sequence requirements to obtain the effective unit set of the chain structure.

[0034] The path structure generation submodule calls the set of valid units of the chain structure, writes each unit into the chain structure index queue according to the path number, constructs the on-chain path mapping relationship table, and generates the on-chain transaction traceability path structure.

[0035] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0036] In this invention, a stability score is calculated based on the differences in field call order, call interval, and call return content in the node access behavior log. Nodes with stable access behavior are selected to form a block access permission mapping. Sorting tags are constructed based on transaction timestamps and transaction amounts to prioritize concurrent transactions, resolving the disorder of concurrent write order. Joint analysis of the control level, path identifier, and validity period in access credentials is performed to determine the read / write permission levels for on-chain data access, achieving fine-grained control of transaction access permissions. Dynamic matching and judgment are performed using a public key address list and multi-signature access thresholds to form a link access path redirection, reducing the possibility of node data tampering. Sequence verification and index tracing are performed based on the chain segment block height, relay node confirmation status, and terminal data field changes, significantly improving the traceability capability of financial transaction data, ensuring the consistency and accuracy of data structures, reducing the risk of misjudgment and resource consumption during financial business regulatory audits and risk assessments, and improving the overall efficiency and security of financial data processing. Attached Figure Description

[0037] Figure 1 This is a system flowchart of the present invention;

[0038] Figure 2 This is a flowchart of the access chain authorization module of the present invention;

[0039] Figure 3 The flowchart for the arbitration scheduling module of this invention is shown below;

[0040] Figure 4 This is a flowchart of the credential path identification module of the present invention;

[0041] Figure 5 This is a flowchart of the callback node module of the present invention;

[0042] Figure 6 This is a flowchart of the chain-result output module of the present invention. DETAILED DESCRIPTION

[0043] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application.

[0044] In the description of the present application, it should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only used to facilitate the description of the present application and simplify the description, and therefore cannot be understood as indicating or implying that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application. In addition, in the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise explicitly and specifically limited.

[0045] Please refer to Figure 1 The present application provides a technical solution: a financial data processing system based on a block chain, the system comprising:

[0046] The access chain authorization module obtains the access behavior log record of the node within three periods, including transaction detail record, account balance change value and credit risk score, calculates the access stability score based on the field calling sequence difference value, calling interval time difference value and calling return content consistency proportion, compares the access stability score with the preset access stability benchmark value, screens the nodes with a score greater than the benchmark value, and generates a block access permission mapping group;

[0047] The write arbitration scheduling module calls the block access permission mapping group, constructs a sorting tag combining the transaction timestamp, network delay time, block packaging time consumption and fund transaction amount of each transaction data, calculates the priority score according to the transaction timestamp and fund transaction amount, compares the order according to the priority score to build a write queue, sorts the concurrent transaction write requests, and generates a multi-node transaction write sequence queue;

[0048] The transaction timestamp indicates the specific time when the transaction is created or submitted, and the format is UTC standard time; the network delay time refers to the network transmission time required from sending to receiving between nodes, which can be measured by round-trip time; the block packaging time consumption refers to the average processing time of the verification node for packaging the transaction into a block; the fund transaction amount is the actual value of the fund change in the transaction, which is used to measure the degree of influence of the transaction;

[0049] The credential path identification module calls the multi-node transaction write order queue, extracts the access control level, resource path identification code, and valid time range in the access credential according to each transaction record, reads the three fields in combination, and then compares them with the data sensitivity level label of the on-chain data structure in turn to determine whether the access control level is less than the data sensitivity level label. If it is less than, it is set as a read-only chain identification, and if it is greater than or equal to, it is set as a full-chain tracing identification. The chain access label set generated by the comparison is combined to generate a credential-driven chain path label set;

[0050] The access control level indicates the data type or range that the credential allows to access, which is usually multi-level classification, such as public, restricted, confidential, etc.; the resource path identification code is a resource address code or smart contract call path; the valid time range represents the valid use time period of the credential, which is defined in the start-end time format; the data sensitivity level label is defined according to the data type in terms of compliance, privacy, and risk, which is generally divided into non-sensitive, internal sensitive, and confidential levels;

[0051] The structure callback node module calls the credential-driven chain path label set, reads the node public key address list in the path according to the path record marked with the full-chain tracing identification, compares it with the access control level in the access credential, determines whether it meets the multi-signature access threshold value set in the link, appends a path redirection mark if it does not meet the threshold value, constructs a path state list, and generates an access chain redirection structure group;

[0052] The node public key address list is the address of the participating verification node stored and registered in the blockchain network; the multi-signature access threshold value is the minimum number of joint verifications required for accessing data under the multi-signature mechanism, which is commonly set as 2 / 3 or 3 / 5;

[0053] The chain result output module calls the access chain redirection structure group, extracts the chain segment start block height, relay node confirmation status code, and end data field change value from the record marked as a valid path structure, performs structure order verification on the three fields, writes them into the chain structure index queue, and generates an on-chain transaction tracing path structure;

[0054] The chain segment start block height is the chain height of the first block in the path verification, which is used to confirm the data source starting point; the relay node confirmation status code is the status set returned by the relay node verification transaction, which is commonly 0 (not confirmed), 1 (confirmed), or 2 (confirmed); the end data field change value refers to the change amplitude of key fields such as amount and account value in the last block, which is used to trace back to determine whether the data has been rewritten;

[0055] The block access permission mapping group includes a node behavior continuity score record, a node periodic access stability label, and a permission allocation level table, the multi-node transaction writing order queue includes a sorting priority label set, a cross-node time scheduling index, and a transaction conflict mediation identifier, the credential-driven chain path label set specifically is a chain access control mark, a path selection level identifier, and a credential matching path correspondence table, the access chain redirection structure group includes a redirection path mapping table, a path verification failure index, and a chain segment access fallback node set, and the on-chain transaction tracing path structure specifically refers to a chain data tracing path, a structure consistency mapping sequence, and an output data change mapping graph.

[0056] Please refer to Figure 2 The access chain authorization module includes:

[0057] The behavior log collection submodule acquires the access behavior logs of the nodes in three consecutive periods, calls three data fields of transaction details records, account balance changes, and credit risk scores, establishes an access record set according to the time sequence of the occurrence of the access behaviors, and archives the records according to the data source nodes to generate an access behavior log summary table;

[0058] The access behavior logs of the nodes in three consecutive periods are acquired, and a log set can be established for the access records of the transaction fields of the blockchain nodes in different time segments, three field data of transaction details records, account balance changes, and credit risk scores are collected, wherein the transaction details records are stored in the form of original sequence numbers of field submission, the account balance changes are represented by the amount difference of continuous account changes, and the credit risk scores are collected in the form of standardized scores of the nodes in an external rating system, for example, for the nodes , the transaction field sequence is 1, 2, and 3, the corresponding code is 1, the account change is from +100 in the first period to +300 in the third period, and the credit risk score is 72 points, the sequence is arranged with the node timestamp as an index, such as , to form a periodic access data structure, then the logs are sorted in ascending order according to the timestamp field, and a node label is established according to the node number associated with each record to achieve identifiable archiving of the data sources, and finally an access behavior log summary table is generated;

[0059] The stability score calculation submodule extracts the data call sequence, call time interval, and result return content associated with each node based on the access behavior log summary table, respectively calculates the field sequence difference value, interval difference value, and result consistency proportion, and uses the formula:

[0060] ;

[0061] The operation obtains a list of access stability score values, establishes a score distribution set according to the concentration degree of the score values, and obtains a node stability score set;

[0062] wherein, represents the access stability score, reflecting the quantified score of the stability of node behavior, represents the actual call order encoding value of the field in the behavior log, represents the standard call order encoding value of the field set by the system, represents the timestamp of the access behavior, represents the timestamp of the access behavior, represents the maximum time interval in all access behaviors, used for normalization processing of the time interval, represents the number of times of changes in the returned results in the access behavior, represents the total number of times of result returns in the access behavior, represents the number of access behaviors in the period, used as the upper limit index in the cumulative term;

[0063] Based on the access behavior log summary table, the field order number, continuous access timestamp and returned field value of each node in the period are extracted, and three factors of order number difference, time interval normalized sum of squares and result consistency proportion are calculated, wherein the order difference adopts The difference term is calculated, if the actual call field order of the node is , and the standard order is , then the difference is 1, the time interval normalization part adopts the maximum time interval standardization, if the timestamp of the node is , then , the normalized expression is , the change consistency is calculated by the ratio of the number of result changes and the total number of returns , assuming that the number of times of return value changes of the node is , and the total number is , then the consistent proportion is , and the final access stability score formula is:

[0064] ;

[0065] Substitute the node parameters:

[0066] , , , , ;

[0067] The time item is:

[0068] ;

[0069] The access stability score is:

[0070] ;

[0071] To display the stability score results for all nodes, the following data table is generated:

[0072] Table 1 Node Access Stability Scoring Table

[0073]

[0074] As shown in Table 1, the lower the score, the more continuous and stable the access behavior.

[0075] Set baseline value This value comes from all nodes in the sample set. The scores are calculated based on the 25th percentile below the mean, and dynamically adjusted as the sample size changes to avoid concentration bias and ensure the standard can distinguish between stable access nodes and highly variable nodes. The calculation reference is set as follows: if the mean score of the sample set is 0.7 and the standard deviation is 0.12, then... To enhance the conservatism of the screening, the value can be increased to 0.75 to ensure applicability;

[0076] The node permission filtering submodule calls the node stability score set, compares the score of each node with the set access stability benchmark value, selects nodes with a score value higher than the benchmark value, marks the access permission level, constructs a node permission mapping sequence, and generates a block access permission mapping group.

[0077] Call the node stability score set to classify the nodes , , The corresponding scores are compared with the set access stability benchmark value in turn. The comparison was made, and the result was... , , Nodes with scores below the benchmark are considered qualified and are marked. To grant access, the node is assigned the permission level as Level 1. The node number, permission level, and score are written into the permission mapping sequence. Other nodes are labeled "frozen" and marked as "rejected" in the mapping table, ultimately resulting in the block access permission mapping group. This result demonstrates that, with a set baseline value... Under the filtering strategy, only nodes It meets the requirements for access stability and has inbound link permissions.

[0078] Please see Figure 3 The following are written to the arbitration scheduling module:

[0079] The time label extraction submodule calls the block access permission mapping group to obtain the transaction timestamp, network delay time, block packaging time consumption, and fund transaction amount corresponding to the transaction data, matches the fields with the node identifier in the block access permission mapping group, and establishes a field comparison table between the transaction record and the node to obtain a transaction parameter matching set;

[0080] The transaction timestamp, network delay time, block packaging time consumption, and fund transaction amount corresponding to the transaction data are respectively denoted as parameters 、 、 、 The parameter values are matched with the node identifier in the block access permission mapping group, and each transaction number is one-to-one corresponding to the node number to generate a field comparison relationship table, such as transaction number TX1 corresponding to node N1, and the field value is seconds、 yuan、 milliseconds、 milliseconds, the parameter comparison table is established to complete the transaction structure construction, and a transaction parameter matching set is obtained;

[0081] The priority score calculation submodule calls the transaction parameter matching set to normalize the difference values of the fields, and uses the formula:

[0082] ;

[0083] The priority score value of the transaction is obtained by operation, and a transaction priority score set is generated;

[0084] Wherein, represents the priority score value of the th transaction, represents the normalized value of the transaction timestamp of the th transaction, represents the normalized value of the fund transaction amount of the th transaction, represents the normalized value of the network delay time of the th transaction, represents the normalized value of the block packaging time consumption of the th transaction;

[0085] Each transaction record in the transaction parameter matching set is called to normalize 、 、 、 four original data, respectively using the maximum value normalization method, wherein the maximum timestamp is , the maximum amount is yuan, and the maximum delay is milliseconds, maximum packing time consumption milliseconds; perform normalization operation on TX1 transaction record:

[0086]

[0087]

[0088]

[0089]

[0090] Substitute into the priority score calculation formula:

[0091]

[0092] In this way, TX2 and TX3 are calculated in the same way to obtain their corresponding scores.

[0093] The formula has the advantage that by setting the delay time and the packing time consumption as the denominator to construct an anti-interference factor, it can suppress the priority distortion caused by high delay, and at the same time, by multiplying the timestamp and the amount value to amplify the priority of early large transactions, it helps to coordinate the concurrent processing rhythm.

[0094] The actual data results are as follows:

[0095] Table 2 Transaction Priority Score Table

[0096]

[0097] Referring to Table 2, the score results show that TX1 has the highest priority, followed by TX3, and finally TX2, which meets the strategy goal of processing early large transactions first. Based on the score value interval, the transaction numbers can be arranged in descending order to establish a priority index table.

[0098] The sorting queue generation submodule generates a sorting index of the corresponding node identifier and transaction ID based on the transaction priority score set, arranges the transaction numbers in descending order according to the score values of each transaction, and constructs a transaction record sorting table to obtain a multi-node transaction write order queue.

[0099] Based on the score values recorded in the transaction priority score set, the value is called to arrange the transaction numbers in descending order, and an index relationship table is constructed to record the write order between the transaction numbers and the node identifiers. For example, the priority score of TX1 is 0.8944, the priority score of TX3 is 0.7809, and the priority score of TX2 is 0.5667. The order is TX1, TX3, and TX2 in turn. Assuming that node N1 processes TX1, N2 processes TX2, and N3 processes TX3, the order mapping in the sorting index table is , ,​​​​​ Finally, the multi-node transaction write order queue is obtained. The result shows that under the normalized score calculation, the transaction is assigned a priority order value, supporting the construction of a controllable scheduling mechanism and completing the node task allocation.

[0100] Please refer to Figure 4 The credential path identification module includes:

[0101] The field extraction submodule calls the multi-node transaction write order queue, extracts the access control level, resource path identification code, and effective time range three fields in the access credential, writes the field values into the uniform structure index table and identifies them according to the transaction number, and generates a credential field index set;

[0102] Each transaction record in the multi-node transaction write order queue is called to extract its attached access credential content one by one. The extracted fields include the access control level, the resource path identification code, and the effective time range. The access control level is represented by a level value, and the level is divided from 0 to 3, representing public, restricted, internal, and confidential in turn. For example, transaction number TX1 corresponds to an access control level of 1, indicating restricted access. The resource path identification code is the data block path address it intends to access, such as " / ledger / block / 04523". The effective time range is represented by a timestamp interval, such as , ] indicates that the credential is valid between 13:00 and 14:00 on October 1, 2021 Beijing time. If the transaction timestamp falls within this interval, it is considered valid. The above three fields are called and combined to write into the uniform structure index table, and are identified and recorded according to the transaction number. Finally, the credential field index set is obtained.

[0103] The level comparison submodule reads the data sensitivity level label in the on-chain data structure based on the credential field index set according to the access control level corresponding to each transaction credential, compares the two field values in order, judges whether the access control level is less than the data sensitivity level label, and marks the comparison result state to obtain the credential level comparison result set.

[0104] According to the access control level corresponding to each transaction in the credential field index set, the sensitive level label corresponding to the requested data is read from the on-chain data structure database, which is defined as a four-level permission requirement level, respectively 0 (public), 1 (restricted), 2 (internal), and 3 (confidential), and the fields are sorted according to the integer value and compared, such as TX1 access control level is 1, and the path data sensitive level is 2, then 1 < 2, it is judged that the access level is insufficient; otherwise, if TX2 access control level is 2 and data sensitive level is 1, it is determined that the authorization is covered, and after the comparison operation is performed, if the comparison is successful, the state is marked as "match", and if the comparison fails, the state is marked as "not match", all transactions are compared, a comparison state record list is formed, and finally a credential level comparison result set is generated; such as TX1 comparison fails, TX2 comparison succeeds, and TX3 comparison fails, the record structure is as follows:

[0105] Table 3: Credential level comparison record table

[0106]

[0107] As shown in Table 3, through field level comparison, a structured comparison marking value is formed, which lays a foundation for subsequent chain path marking generation;

[0108] The path marking generation submodule assigns a read-only chain identifier to the records whose access control level is lower than the data sensitive level label according to the credential level comparison result set, and assigns a full-chain trace identifier to the remaining records, classifies and combines the two types of chain access labels, and generates a credential-driven chain path label set;

[0109] According to the comparison state recorded in the credential level comparison result set, the label value is assigned to each transaction number, if the control level of the transaction credential is lower than the target field sensitive level, that is, the comparison state is "not match", it is marked as a read-only chain identifier, which means that the transaction node can only read part of the summary information and does not have the right to trace the chain; if the comparison state is "match", it is marked as a full-chain trace identifier, which means that the complete path chain data is allowed to be called, and then the two types of identifier labels are combined and written into the chain label structure mapping table, such as TX1 and TX3 are assigned a read-only chain identifier, and TX2 is assigned a full-chain trace identifier, and finally a credential-driven chain path label set is generated. The structure supports the pointing decision of the subsequent on-chain access path, and realizes the complete connection of the access verification module and the chain link control logic.

[0110] Please refer to Figure 5 , the structure callback node module includes:

[0111] The chain path extraction submodule calls the credential-driven chain path label set, reads the node public key address list in the associated path according to the path record marked as full-chain trace, and archives them in order to generate a node link address set;

[0112] The path records marked as full-chain tracking in the call credential drive chain path label set are recorded, the node chain segment paths associated in each record are parsed and extracted, all the node public key address information on the path is read, the node address is represented in compressed encoding format, such as 0x3a9c…, after parsing, the numbering is arranged in access order and the archiving operation is completed, for example, the path record PATH_01 involves node address order , then its path length is 3, this structure directly affects the minimum joint verification threshold required when accessing, after reading all the path addresses, the node address list in each path is written into the structured path table with transaction number as index, forming the path and node mapping relationship, and finally generating the node link address set;

[0113] The permission verification submodule obtains the access control level parameter in the access credential according to the node value of each path based on the node link address set, compares it with the multi-signature access threshold value set by the link, and uses the formula:

[0114] ;

[0115] The operation obtains the path permission offset degree, judges whether the offset degree exceeds the access offset tolerance range value, if it exceeds, marks the verification failure state, and obtains the permission matching offset degree sequence;

[0116] Wherein, represents the path permission offset degree, represents the access control level value in the credential, represents the multi-signature access threshold value corresponding to the link, represents the node public key address value in the path, represents the The average access delay normalization value of the node in the path, represents the The path jump frequency normalization value of the path in the chain network, is the regulation factor after the growth compression adjustment of the path jump frequency, is used to represent the nonlinear increase and decrease relationship of the number of nodes to the access threshold difference;

[0117] According to the number of nodes contained in each path in the node link address set, the path length parameter is extracted, and the access control level value in the credential structure is read, the multi-signature access threshold value of the path is set to match, the threshold value is calculated according to the number of path nodes times the threshold proportion coefficient Set to 0.7, according to the system settings in the processing of multi-sign access scene requires more than 70% of the node joint signature can be authorized, to protect the security and decision constraints, threshold rounding up to deal with, that is: , where the proportion coefficient is a system fixed parameter, not fluctuate with the path, but the final With The value fluctuates, when the path length increases Synchronous rise; if the number of nodes , then , then the average access delay normalization value is calculated after collecting the average response time of each node in the path , such as node response time is 210, 180, 240, 150 milliseconds, the normalized reference value is the maximum response value 240 milliseconds in the path, , the path jump frequency is the frequency of switching in the chain network scheduling table per hour, set to 5 times, the maximum jump standard is 15 times, , the authority offset degree is calculated by substituting the formula:

[0118] ;

[0119] The offset tolerance range value (access offset threshold) is set to 0.1, which is the boundary value of the system fault tolerance range. Referring to the maximum value of the 90% distribution segment of the multi-path link average offset degree, it reflects the maximum acceptable difference between the path authorization and the actual certificate level under the influence of time and jump frequency. If , it is considered to exceed the tolerance, and is recorded as a rejection state, and finally the authority matching offset degree sequence is obtained;

[0120] The path state construction submodule calls the authority matching offset degree sequence, records the path record marked as verification failure, and appends the path redirection mark after the path identification. Update the path state index table, construct the path state set according to the path order, and generate the access chain redirection structure group.

[0121] Call the record state field in the authority matching offset degree sequence, process the path record with the state "reject", read the original path label structure, append the path redirection mark at the end of the path identification, such as marking "→ALT_PATH_03" after PATH_01, and write the redirection target path into the path redirection table to establish the path mapping replacement relationship. The updated record structure is written into the path state index table, and the index pointer structure is generated according to the transaction number and the original path order. Finally, the access chain redirection structure group is obtained, which is used as the data input basis for the subsequent path selection and resource scheduling module.

[0122] Please refer to Figure 6 , the chain result output module includes:

[0123] The field extraction submodule calls the access chain redirection structure group, extracts the chain segment starting block height, relay node confirmation status code, and end data field change value according to the records marked as valid path structures, reconstructs the three fields into structure units in the path order, and generates the chain structure field set;

[0124] All record paths in the access chain redirection structure group are called, and entries marked as "valid path structures" are filtered out. These paths are considered to have passed verification and have traceability availability. Three key fields of the chain segment, the chain segment starting block height, the relay node confirmation status code, and the end data field change value, are extracted. The starting block height represents the starting position on the chain in the form of an integer, such as block height 64231 indicating that the path starts at block 64231. The relay node confirmation status code is an integer value of 0, 1, or 2, corresponding to unconfirmed, processing, and confirmed states, respectively. The field change value is represented by the absolute value of the difference, for example, a financial indicator item in the end field changes from 623.11 to 634.57, and the change value is 11.46. After extracting the above three fields, they are arranged into structure units in the path order and written into the structure set, indexed by the path number, and finally the chain structure field set is generated.

[0125] The order verification submodule verifies the block height, relay status, and data change value in each structure unit according to the chain structure field set, judges whether the block height is the path starting index, whether the relay status is continuously increasing, and whether the data change value is less than the preset change tolerance value, filters the structure units that meet the order requirements, and obtains the chain structure valid unit set.

[0126] According to the chain structure field set, the in-order checking processing is sequentially performed on each structure unit, first, it is judged whether the block height meets the starting index standard of path order, the starting block height lower limit is 60000, if the path number is PATH_04, the starting block height of the first field is 64231, which meets the requirement; then, it is checked whether the relay state is continuously increased, that is, for the relay nodes passed in the path, the confirmation state code should be sequentially from 0 to 2 or remain consistent and irreversible jump; then, the size of the change value of the terminal field is analyzed, if the field value change amplitude exceeds the set tolerance value, it is regarded as an abnormal record, the upper limit of the field change tolerance is set to 15.00, the change tolerance value is derived from the 80% distribution upper limit of the 30-day monitoring field change range central interval in the financial data tracing, the reference field is a typical volatility financial indicator (such as price change, balance fluctuation), after taking the average value in multiple measured paths, the weighted setting is made, such as the terminal field change value of PATH_04 is 11.46, which is lower than 15.00, then it is judged, the block height of PATH_05 is set to 58200, which does not meet the starting block standard, the relay state of PATH_06 is not continuous, the field change value of PATH_07 is 19.63, which is over limit, then after screening, only PATH_04 meets all the in-order standards, the valid unit set of chain structure is finally screened out and composed; the role of the valid unit set is to provide node-level input basis for subsequent construction of complete traceable path, to avoid path graph distortion caused by data structure misplacement or field jump;

[0127] The path structure generation submodule calls the chain structure valid unit set, writes each unit into the chain structure index queue according to the path number, constructs the chain path mapping relationship table, and generates the chain transaction traceable path structure;

[0128] The structure unit in the chain structure valid unit set is called, the structure order number processing is performed according to the path number belonging to it, and the path number, starting block height, relay state and field change value in each structure unit are written into the chain structure index queue according to the unified structure format, the mapping index link between structure nodes is completed, then the path node aggregation operation is performed in the structure index queue, to unify the chain segment structure to interface into a complete path mapping structure, finally, the graph data record result is generated, which is output as a structure path graph information package, as a system data traceable display output format, the chain transaction traceable path structure is constructed, the path mapping entries of the structure can be called for subsequent display and data comparison.

[0129] The above merely describes the preferred embodiments of the present application, and is not intended to limit the present application in other forms. Any skilled person in the art can modify or change the disclosed technical content into equivalent embodiments with equivalent changes, and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present application, without departing from the technical solution content of the present application, still falls within the protection scope of the present application.

Claims

1. A blockchain-based financial data processing system, characterized in that, The system includes: The access chain authorization module obtains the access behavior log records of nodes within three periods. Based on the difference value of field call order, the difference value of call interval time, and the consistency ratio of call return content, it calculates the access stability score, filters nodes with scores greater than the benchmark value, and generates a block access permission mapping group. The access chain authorization module includes: The behavior log collection submodule obtains the access behavior logs of nodes within three consecutive periods, calls three data fields: transaction details, account balance change value, and credit risk score, establishes an access record set according to the time sequence of access behavior, and identifies and archives the data according to the data source node to generate an access behavior log summary table. The stability score calculation submodule extracts the data call order, call time interval and result return content associated with each node based on the access behavior log summary table, calculates the field order difference value, interval difference value and result consistency ratio respectively, calculates and obtains the access stability score value list, establishes a score distribution set according to the concentration of score values, and obtains the node stability score set. The node permission filtering submodule calls the node stability score set, compares the score of each node with the set access stability benchmark value, selects nodes with a score value higher than the benchmark value, marks the access permission level, constructs a node permission mapping sequence, and generates a block access permission mapping group. The arbitration scheduling module calls the block access permission mapping group, calculates the priority score according to the transaction timestamp and the transaction amount, compares the priority scores in order to build a write queue, and generates a multi-node transaction write order queue. The credential path identification module calls the multi-node transaction writing order queue, determines whether the access control level is less than the data sensitivity level label, if it is less than, it is set as a read-only chain identifier, if it is greater than or equal to, it is set as a full-chain traceability identifier, and generates a credential-driven chain path label set. The structure callback node module calls the credential-driven chain path tag set, compares it with the access control level in the access credential, and determines whether the multi-signature access threshold value set in the link is met. If it is not met, a path redirection flag is added, a path status list is constructed, and an access chain redirection structure group is generated.

2. The blockchain-based financial data processing system according to claim 1, characterized in that, The block access permission mapping group includes node behavior continuity score records, node periodic access stability labels, and permission allocation level tables. The multi-node transaction write order queue includes a sorting priority label set, a cross-node time scheduling index, and a transaction conflict mediation identifier. The credential-driven chain path label set specifically includes chain access control markers, path selection level identifiers, and a credential matching path lookup table. The access chain redirection structure group includes a redirection path mapping table, a path verification failure index, and a chain segment access rollback node set.

3. The blockchain-based financial data processing system according to claim 2, characterized in that, The write arbitration scheduling module includes: The time tag extraction submodule calls the block access permission mapping group to obtain the corresponding transaction timestamp, network latency, block packaging time, and fund transaction amount in the transaction data. It matches the fields with the node identifiers in the block access permission mapping group and establishes a field mapping table between transaction records and nodes to obtain the transaction parameter matching set. The priority score calculation submodule calls the transaction parameter matching set, normalizes the difference values ​​of the fields, calculates and obtains the priority score value of the transaction, and generates a transaction priority score set. The sorting queue generation submodule, based on the transaction priority score set, sorts the transaction numbers in descending order according to the score value of each transaction, generates a sorting index of corresponding node identifier and transaction ID, constructs a transaction record sorting table, and obtains a multi-node transaction writing order queue.

4. The blockchain-based financial data processing system according to claim 3, characterized in that, The credential path identification module includes: The field extraction submodule calls the multi-node transaction writing order queue to extract three fields from the access credential: access control level, resource path identifier code, and valid time range. The field values ​​are written into a unified structure index table and classified and identified by transaction number to generate a credential field index set. The level comparison submodule, based on the certificate field index set, reads the data sensitivity level label in the on-chain data structure according to the access control level corresponding to each transaction certificate, compares the values ​​of the two fields in sequence, determines whether the access control level is less than the data sensitivity level label, marks the comparison result status, and obtains the certificate level comparison result set. The path tag generation submodule assigns read-only chain tags to records with access control levels lower than data sensitivity level tags based on the credential level comparison result set, and assigns full-chain traceability tags to the remaining records. It then categorizes and combines the two types of chain access tags to generate a credential-driven chain path tag set.

5. The blockchain-based financial data processing system according to claim 4, characterized in that, The structure callback node module includes: The chain path extraction submodule calls the credential-driven chain path tag set, reads the list of node public key addresses in the associated path based on the path records marked as full-chain traceability, and archives them in the path order to generate a node link address set; The permission verification submodule, based on the node link address set, obtains the access control level parameter in the access credential according to the node value of each path, compares it with the multi-signature access threshold value set for the link, calculates the path permission offset, and determines whether the offset exceeds the access offset tolerance range value. If it exceeds, it marks the verification failure state and obtains the permission matching offset sequence. The path state construction submodule calls the permission matching offset sequence, appends a path redirection flag to the path identifier based on the path record marked as verification failure, updates the path state index table, constructs a path state set in path order, and generates an access chain redirection structure group.

6. The blockchain-based financial data processing system according to claim 5, characterized in that, The system also includes: The chain result output module calls the access chain redirection structure group to extract the chain segment start block height, relay node confirmation status code, and end data field change value from the records marked as valid path structures. It performs structure order verification on the three fields and writes them into the chain structure index queue to generate the on-chain transaction traceability path structure. The on-chain transaction traceability path structure specifically refers to the chain-style data traceability path, the structural consistency mapping sequence, and the output data change mapping diagram.

7. The blockchain-based financial data processing system according to claim 6, characterized in that, The chained result output module includes: The field extraction submodule calls the access chain redirection structure group, and extracts three fields—chain segment start block height, relay node confirmation status code, and end data field change value—based on the records marked as valid path structures. The three fields are then reconstructed into structural units according to the path order to generate a chain structure field set. The sequence verification submodule sequentially numbers the block height, relay status, and data change value in each structural unit according to the chain structure field set, determines whether the block height is the starting index of the path, whether the relay status is continuously increasing, and whether the data change value is less than the preset change tolerance value, and filters the structural units that meet the sequence requirements to obtain the effective unit set of the chain structure. The path structure generation submodule calls the set of valid units of the chain structure, writes each unit into the chain structure index queue according to the path number, constructs the on-chain path mapping relationship table, and generates the on-chain transaction traceability path structure.

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